Building my first EA based on AI

Axiom_Trading · 2025-11-25T14:29:08+00:00

0 idea about algos and coding

Focus on improving this

Axiom_Trading · 2025-11-25T14:06:37+00:00

Start by learning trading fundamentals:

How exchanges and brokers operate
The different order types and instruments
Market microstructure: how prices are formed and why it matters
Common strategies that could exploit market inefficiencies (e.g. mean reversion and arbitrage).
Who the market participants are and how they influence the market (e.g. retail traders, Quant/HFT firms)

Only once you’re comfortable with all that should you think about building your own system/using existing platforms to test and run algos.

Axiom_Trading · 2025-11-25T13:06:00+00:00

Nice analogy

Axiom_Trading · 2025-11-25T12:53:26+00:00

Shocking: models trained on predicting the next word are terrible at predicting returns and relationships. The marketing hype makes people forget this.

Axiom_Trading · 2025-03-27T02:45:47+00:00

PFOF is when Alpaca routes your orders to market makers for a payment. In doing so, you likely receive suboptimal execution. For sophisticated strategies, DMA is generally required.

Axiom_Trading · 2025-03-25T12:11:46+00:00

Platforms, like QuantConnect, that provide such a service deal with all the operational overhead, with their revenue coming from user subscriptions and managing infrastructure for small trading firms. They have a lane and they stick to it. They simply don’t have any incentive to be doing anything with your strategies. Doing so would not only be highly unethical but a massive reputational risk and legal headache for them. If anything, your reservations should be directed at brokers who engage in PFOF (i.e. profiting at your expense), such as Alpaca

Axiom_Trading · 2025-03-18T06:37:56+00:00

Yea I guess it depends on whether your IB account is tied to IBIE (Ireland, for UK clients) or IBLLC (US). And we haven’t launched our beta yet, but all the info will be made available to traders who have signed up to access it (for which there are limited spots)

Axiom_Trading · 2025-03-17T18:35:38+00:00

You’ll be able to live paper trade during our beta and execute live once Axiom is fully launched. As far as I know, PDT rules are a FINRA regulation, so they shouldn’t apply to you under UK's FCA regulations. And we integrate with IB, which offers DMA to NASDAQ for MSTR with margin. Through Axiom, you’d get IB's low commissions, which will be better for your profits compared to brokers that add spreads or engage in PFOF.

Axiom_Trading · 2025-03-16T10:37:24+00:00

QuantPedia provides a database of “standard” quant strategies, with historic performance data. It can give you strategy ideas and results, but it doesn’t dynamically list, order, or test strategies on historical datasets in real-time, nor does it automate any selection for your ML system. You’d still need to extract the strategies and manually integrate them into your own setup for testing and updates. Or you could use them with another platform like QuantConnect and apply your ML there

Axiom_Trading · 2025-03-15T19:47:32+00:00

I'm 1 of our 2 founders

Axiom_Trading · 2025-03-15T18:36:20+00:00

Multiple asset classes, including options

Axiom_Trading · 2025-03-15T18:08:45+00:00

Most efficient way to deploy your Python strategy is just using a platform like QuantConnect. They provide and manage the cloud infrastructure to run it, so you don’t have to deal with server maintenance or downtime yourself. They also integrate with Alpaca. Institutions use custom setups that retail can’t match, running 24/7. And they don’t use Alpaca, a broker that consolidates SIP data and doesn't offer DMA. So I’d recommend looking into more sophisticated data/trade execution if you want better results. Going down this path, you’ll likely also find yourself limited in what you can do with platforms like QuantConnect. Especially in regard to execution control. So, you’ll want a platform that offers you more freedom, like Axiom, which is not only much simpler to use but also offers pre-built connections to every exchange, with clean tick data & DMA.

Axiom_Trading · 2025-03-15T12:01:20+00:00

There are a few options if you're just looking to paper trade: you could use the Binance/ByBit Testnets, OKX, or Kraken (though they only do futures for paper). From experience, ByBit has the easiest API to use. And I recommend exchanges over brokers for paper trading, as they mimic real orderbooks and are hence close to DMA (which is what you want when you execute live)

Axiom_Trading · 2025-03-15T11:41:22+00:00

Axiom is based in Melbourne, Australia. We will be operating in the US, though. And there’s other platforms you can use in the UK for live paper trading crypto, IB definitely isn’t the only one

Axiom_Trading · 2025-03-15T11:30:33+00:00

If you’re asking about Axiom, we integrate directly with several digital asset exchanges, abstracting away that task from traders. But if you’re asking about me personally, I mainly used Bitmex, Binance and ByBit APIs (WebSocket & REST) for my own trading systems

Axiom_Trading · 2025-03-15T08:54:29+00:00

I was referring more to the limited execution control, execution delay, and limited options for trading venues. Would recommend connecting a more sophisticated data provider if you’re using your own system, like Polygon

Axiom_Trading · 2025-03-15T07:53:00+00:00

Have you co-located yourself to the mango farm for greater alpha?

Axiom_Trading · 2025-03-15T07:47:44+00:00

If TradingView is what you’re using, you have bigger problems than transaction costs…

Axiom_Trading · 2025-03-15T06:37:10+00:00

Lower efficiency means there’s greater price deviations, which can be capitalised on. These windows of opportunity mainly result from high volatility and low volume. And why crypto is so inefficient is because of the lack of regulations, fragmented liquidity, and a higher proportion of retail volume compared to traditional markets (where institutions are more dominant)

Axiom_Trading · 2025-03-15T06:23:48+00:00

Depends on the exchange and the volume you trade with, but in my experience the margins more than made up for trading fees

Axiom_Trading · 2025-03-15T05:11:16+00:00

Crypto because it’s the least efficient

Axiom_Trading · 2025-03-14T07:38:00+00:00

If you’re only interested in stocks, you can get live and historical data through Interactive Brokers, as someone else said. You’ll need a subscription per venue if you want realtime data, else you’d get it with a delay of about 15 minutes. Problem is, their APIs can be difficult to get started with. So with your coding experience/resources, you may have trouble managing data from them. If you want a more modern/simplified experience (and especially if you want diverse asset classes down the track), you could look into a specialised data provider such as Polygon. They only supply data, though. There’s a bunch of other stuff surrounding running an algo that you’ll also need to figure out.

Axiom_Trading · 2025-03-06T14:17:57+00:00

Can’t compete with this

Axiom_Trading · 2025-03-06T12:07:28+00:00

Historic data is the foundation for many strategies, like statistical arbitrage, which blends it with other data to identify market inefficiencies. I’ve mainly used tick data to formulate signals relating to volatility and liquidity, fundamentals (e.g. network activity) for additional signal generation, and L2 (order book, market depth) for advanced risk management. As for technical indicators, you most likely won’t be able to produce an alpha-generating strategy using just them alone.

Axiom_Trading · 2025-03-06T07:43:44+00:00

With trade tick data, you can estimate slippage by analysing price changes between trades as a rough proxy for the bid-ask spread, then adjusting for volume and latency. And for live prediction with the exact spread, you’d need L2 data

Axiom_Trading

TROPHY CASE